Instructions to use textattack/bert-base-uncased-RTE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use textattack/bert-base-uncased-RTE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="textattack/bert-base-uncased-RTE")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("textattack/bert-base-uncased-RTE") model = AutoModelForSequenceClassification.from_pretrained("textattack/bert-base-uncased-RTE") - Inference
- Notebooks
- Google Colab
- Kaggle
Update training_args.bin
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training_args.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:24b2bb6c082efcc9b5a8c1dbf0f62d065ab5c72c4847cb8ebf42edd5efca94e7
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size 1051
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